CN106546966B - Radar noise power estimation method under clutter background based on fitting of a polynomial - Google Patents
Radar noise power estimation method under clutter background based on fitting of a polynomial Download PDFInfo
- Publication number
- CN106546966B CN106546966B CN201610964932.7A CN201610964932A CN106546966B CN 106546966 B CN106546966 B CN 106546966B CN 201610964932 A CN201610964932 A CN 201610964932A CN 106546966 B CN106546966 B CN 106546966B
- Authority
- CN
- China
- Prior art keywords
- pulse
- echo signal
- multiplied
- coherent accumulation
- radar echo
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 230000001427 coherent effect Effects 0.000 claims abstract description 141
- 238000009825 accumulation Methods 0.000 claims abstract description 140
- 239000011159 matrix material Substances 0.000 claims abstract description 131
- 238000005070 sampling Methods 0.000 claims abstract description 30
- 238000012545 processing Methods 0.000 claims description 31
- 230000014509 gene expression Effects 0.000 claims description 18
- 230000001629 suppression Effects 0.000 claims description 10
- 238000009795 derivation Methods 0.000 claims description 2
- 238000012163 sequencing technique Methods 0.000 claims description 2
- 230000002123 temporal effect Effects 0.000 abstract 4
- 230000009466 transformation Effects 0.000 abstract 3
- 238000001514 detection method Methods 0.000 description 9
- 238000004088 simulation Methods 0.000 description 9
- 230000003044 adaptive effect Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000003111 delayed effect Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000003672 processing method Methods 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000002401 inhibitory effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The present invention discloses radar noise power estimation method under a kind of clutter background based on fitting of a polynomial, its main thought are as follows: determine airborne radar, the airborne radar emits pulse signal, and the M × N × L calculated in a coherent accumulation time after M pulse temporal sampling ties up radar echo signal matrix；It calculates separately in a coherent accumulation time after P × L dimension radar echo signal power matrix Y and stagnant the latter PRI in M pulse temporal sampling, P point discrete Fourier after leaf transformation and received P × L ties up radar echo signal power matrix Y' and Y " at N number of array element, L distance unit respectively after leaf transformation in latter two stagnant PRI the latter coherent accumulation time in M pulse temporal sampling, P point discrete Fourier；And then the PL × 1 calculated in sequence the latter coherent accumulation time in M pulse temporal sampling, P point discrete Fourier after leaf transformation ties up radar echo signal matrix Z'；Then matched curve of the element under two-dimentional real number coordinate in Z' is calculated, and then airborne radar noise power under the clutter background based on fitting of a polynomial is calculated.
Description
Technical Field
The invention belongs to the technical field of radar signal processing, and particularly relates to a polynomial fitting-based radar noise power estimation method under a clutter background, which is suitable for estimating noise power in an airborne radar echo signal under the clutter background.
Background
The airborne radar is regarded as a strategic weapon capable of controlling battlefield situations by the military of various countries due to the unique operational characteristics of the airborne radar. Compared with a ground-based radar, the airborne radar is interfered by ground clutter when wide-area target detection or target imaging and other works are carried out due to the influence of platform movement, so that the target detection performance of the radar is reduced, and the interference problem is particularly serious when the airborne radar is in downward-looking work. Because a cluster of clutter signals received by different array element antennas of the phased array airborne radar in an airspace and a cluster of clutter signals received by different pulses in a Coherent Processing Interval (CPI) in a time domain have strong relevance in signal form, namely space-time coupling characteristics, certain traditional moving target detection methods for the ground-based radar, such as three-pulse cancellation processing and pulse-Doppler processing, are difficult to obtain reliable target detection results in a clutter environment.
Under the condition that a clutter plus noise covariance matrix is accurately known, Brennan et al put forward the concept and theory of full space-time two-dimensional adaptive processing (STAP) in 1973, and the idea is to popularize the basic principle of array signal processing into a two-dimensional field formed by pulses and array element sampling; DePietro proposed an Extended Factor Approach (Extended Factor Approach) in 1994 to improve the limitation of space-time adaptive processing on the operand and sample selection, and solved the problem of full space-time two-dimensional adaptive processing on the operand and sample selection to a certain extent by reducing the dimensions of a covariance matrix and a guide vector, so that the method can be applied to actual engineering; after the 21 st century, various algorithms for improving the target detection performance under the clutter background are proposed in succession, and mainly the improvement and the expansion of the extended factorization method.
The above mentioned full space-time two-dimensional adaptive processing and factor-expanding method can improve the detection performance of the airborne radar on the target in a certain application range, but ignores the fact that the power level of the noise component in the output signal after adaptive processing is changed from the noise power level in the received signal, resulting in the reduction of the detection performance of the airborne radar on the target under the condition of the known detectable factor.
Disclosure of Invention
In view of the defects in the prior art, the invention aims to provide a method for estimating the noise power of a radar under a clutter background based on polynomial fitting, and the method for estimating the noise power of the radar under the clutter background based on polynomial fitting can estimate the noise power of the radar under the conditions of stronger clutter power and lower pulse repetition frequency.
In order to achieve the technical purpose, the invention is realized by adopting the following technical scheme.
A method for estimating radar noise power under clutter background based on polynomial fitting comprises the following steps:
step 1, determining an airborne radar, wherein the airborne radar transmits a pulse signal, the pulse repetition time interval of the pulse signal transmitted by the airborne radar is PRI, and the pulse width of the pulse signal transmitted by the airborne radar is TpThe pulse repetition frequency of the airborne radar transmitting pulse signal is PRF; the number of array elements of an antenna array surface of the airborne radar is N, the number of pulses of the airborne radar in a coherent accumulation period is M, the number of maximum unambiguous distance units of the airborne radar is L,calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X after the time domain sampling of M pulses in coherent accumulation time;
step 2, respectively calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X 'received at N array elements and L distance units after M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval and an M multiplied by N multiplied by L dimensional radar echo signal matrix X' received at N array elements and L distance units after M pulse time domain samples in a coherent accumulation time after two pulse repetition time intervals;
step 3, respectively calculating M pulse time domain samples in a coherent accumulation time, a P multiplied by L dimension radar echo signal power matrix Y after P point discrete Fourier transform, M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval, and M multiplied by L dimension radar echo signal matrixes X ' after P point discrete Fourier transform in N array elements and N array elements according to M multiplied by L dimension radar echo signal matrixes X ' after M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval and M multiplied by N dimension radar echo signal matrixes X ' received at N array elements and L distance units after M pulse time domain samples in a coherent accumulation time after two pulse repetition time intervals, and M pulse time domain samples in N array elements after P point discrete Fourier transform, A power matrix Y 'of the P multiplied by L dimensional radar echo signals received at the L distance units, and a power matrix Y' of the P multiplied by L dimensional radar echo signals received at the L distance units, N array elements after P point discrete Fourier transform and M pulse time domain samples in coherent accumulation time after delaying two pulse repetition time intervals; wherein P represents the point number of discrete Fourier transform, and L represents the maximum unambiguous range unit number of the airborne radar;
step 4, carrying out main clutter suppression processing on M pulse time domain samples in the coherent accumulation time, a P multiplied by L dimensional radar echo signal power matrix Y after P point discrete Fourier transform, a P multiplied by L dimensional radar echo signal power matrix Y 'received at N array elements and L distance units after P point discrete Fourier transform and M pulse time domain samples in a coherent accumulation time after lagging a pulse repetition time interval, a P multiplied by L dimensional radar echo signal power matrix Y' received at N array elements and L distance units after P point discrete Fourier transform and M pulse time domain samples in a coherent accumulation time after lagging two pulse repetition time intervals, and obtaining M pulse time domain samples in a coherent accumulation time after main clutter suppression processing and a P multiplied by L dimensional radar echo signal matrix Z after P point discrete Fourier transform, further calculating a PL multiplied by 1 dimensional radar echo signal matrix Z' after M pulse time domain samples and P point discrete Fourier transform in the sequenced coherent accumulation time;
step 5, calculating to obtain a fitted curve of elements in a PL x 1 dimensional radar echo signal matrix Z' subjected to the M pulse time domain samples and the P point discrete Fourier transform in the coherent accumulation time based on least square in a two-dimensional real number coordinate;
and 6, solving the slope of a fitting curve of elements in a PL x 1 dimensional radar echo signal matrix Z' under a two-dimensional real number coordinate after the sorting of M pulse time domain samples and P point discrete Fourier transform based on least square, finding a slope minimum value point, and taking a power value corresponding to the slope minimum value point as airborne radar noise power under a clutter background based on polynomial fitting.
The invention has the beneficial effects that: the method estimates the noise power level in the radar echo signal according to the difference of the power distribution characteristics of clutter components and noise components in the radar echo signal under the clutter background, so that the calculation of the radar echo signal power value of each Doppler-distance unit by using binomial fitting becomes possible, and a three-pulse cancellation method for inhibiting the main clutter is used, so that the method has stronger robustness in a severe clutter environment. Compared with the method which is generally used in the current engineering and used for selecting the range-Doppler data for noise level estimation according to the specific data obtained after pulse-Doppler processing and averagely observing the clear zone level for all range unit powers, the method has better universality and robustness and brings great convenience for the subsequent radar echo signal detection.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a flow chart of a method for estimating radar noise power in clutter background based on polynomial fitting according to the present invention;
fig. 2a is a distribution diagram of power obtained after pulse-doppler processing of radar echo data along a range gate direction and a doppler channel direction, respectively, where the abscissa is a doppler channel number, the ordinate is a range gate number, and each point represents the power magnitude at that location;
fig. 2b is a power distribution diagram obtained after the radar echo data is sequentially subjected to pulse-doppler processing and pulse cancellation processing, wherein the abscissa is a doppler channel number, the ordinate is a range gate number, and each point represents the power of the point;
fig. 3 is a graph of noise power level varying with doppler frequency respectively obtained using different processing methods, i.e., the power distribution of fig. 2a, the power curve of the power distribution of fig. 2b averaged in the distance direction respectively, and the noise power curve estimated using the method of the present invention and the actual noise power curve.
Detailed Description
Referring to fig. 1, it is a flow chart of a method for estimating radar noise power in clutter background based on polynomial fitting according to the present invention; the method for estimating the radar noise power under the clutter background based on polynomial fitting comprises the following steps:
step 1, determining an airborne radar, wherein the airborne radar transmits a pulse signal, the pulse repetition time interval of the pulse signal transmitted by the airborne radar is PRI, and the pulse width of the pulse signal transmitted by the airborne radar is TpThe pulse repetition frequency of the airborne radar transmitting pulse signal is PRF; the number of array elements of an antenna array surface of the airborne radar is N, the number of pulses of the airborne radar in a coherent accumulation period is M, the number of maximum unambiguous distance units of the airborne radar is L,and calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X after the M pulse time domain samples in the coherent accumulation time.
Specifically, an airborne radar is determined, the airborne radar transmits a pulse signal, the pulse repetition time interval of the pulse signal transmitted by the airborne radar is PRI, and the pulse width of the pulse signal transmitted by the airborne radar is TpThe pulse repetition frequency of the pulse signal transmitted by the airborne radar is PRF, and the receiving bandwidth of the airborne radar is B; the number of array elements of the antenna array surface of the airborne radar is N, and the antenna array surfaces of the airborne radar are respectively and uniformly arranged in the pitching direction by N1Array elements, N are uniformly arranged along azimuth direction2Array elements, N ═ N1×N2(ii) a The pulse number of the airborne radar in a coherent accumulation period is M, the maximum unambiguous distance unit number of the airborne radar is L,
the method comprises the following steps of performing time domain sampling on M pulses in a coherent accumulation period of the airborne radar by using N array elements of an antenna array surface of the airborne radar, and calculating to obtain an MXNxL dimensional radar echo signal matrix X after the time domain sampling of the M pulses in the coherent accumulation period, wherein the expression is as follows:
n is 1,2, …, N, L is 1,2, …, L, N represents the number of array elements included in the antenna array of the airborne radar, and M represents the number of pulses of the airborne radar in a coherent accumulation period; recording radar echo signals received at the nth array element and the l-th distance unit after the mth pulse time domain sampling in coherent accumulation time as xm,n,lAnd enabling M to respectively take 1 to M, and further calculating to obtain an M multiplied by 1 dimensional radar echo signal matrix x received at an nth array element and a l distance unit after M pulse time domain samples in coherent accumulation timen,lThe expression is as follows:
which represents the normalized doppler frequency of the doppler signal,v denotes the speed of the airborne radar and λ denotes the wavelength of the electromagnetic wave signal emitted by the airborne radar.
And 2, respectively calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X 'received at N array elements and L range units after M pulse time domain samples within a coherent accumulation time after a pulse repetition time interval and an M multiplied by N multiplied by L dimensional radar echo signal matrix X' received at N array elements and L range units after M pulse time domain samples within a coherent accumulation time after two pulse repetition time intervals.
Specifically, time domain sampling points are delayed by a pulse repetition time interval and two pulse repetition time intervals respectively, and then M pulse time domains in a coherent accumulation time are sampled and then received at an nth array element and an l distance unit to form an M multiplied by 1 dimensional radar echo signal matrix xn,lRespectively carrying out time domain sampling to respectively obtain M multiplied by 1 dimensional radar echo signal matrixes x 'received at the nth array element and the l distance unit after M pulse time domain samples in coherent accumulation time lagging one pulse repetition time interval'n,lAnd M multiplied by 1 dimensional radar echo signal matrix x' received at the nth array element and the l distance unit after delaying M pulse time domain samples in coherent accumulation time after two pulse repetition time intervalsn,lThe expressions are respectively:
when n is 1, respectively taking 1 to L for L, and further respectively obtaining M multiplied by 1 dimensional radar echo signal matrixes x 'received by M pulses at the 1 st array element and L distance units in time domain sampling in coherent accumulation time after a pulse repetition time interval'1And M multiplied by 1 dimensional radar echo signals received at the 1 st array element and L distance units after delaying M pulse time domain samples in coherent accumulation time after two pulse repetition time intervalsNumber matrix x ″)1(ii) a The M x 1-dimensional radar echo signal matrix x 'received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after lagging one pulse repetition time interval'1Is an M x 1 dimensional radar echo signal matrix x 'received at the 1 st array element and the 1 st range unit after M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval'1,1M x 1-dimensional radar echo signal matrix x 'received at 1 st array element and L distance unit after M pulse time domain samples in coherent accumulation time after lagging one pulse repetition time interval'1,L(ii) a M multiplied by 1 dimensional radar echo signal matrix x' received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after delaying two pulse repetition time intervals1The method is characterized in that an M x 1 dimensional radar echo signal matrix x' received at the 1 st array element and the 1 st distance unit after M pulse time domain samples in coherent accumulation time after delaying two pulse repetition time intervals1,1M x 1 dimensional radar echo signal matrix x' received at the 1 st array element and the L-th distance unit after M pulse time domain samples in coherent accumulation time after lagging two pulse repetition time intervals1,L。
Then N is respectively taken from 2 to N, and M multiplied by 1 dimensional radar echo signal matrixes x 'received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after a pulse repetition time interval are obtained respectively'1M x 1-dimensional radar echo signal matrix x 'received at Nth array element and L distance units after M pulse time domain samples in coherent accumulation time after lagging one pulse repetition time interval'NAnd M multiplied by 1 dimensional radar echo signal matrix x' received at the 1 st array element and L distance units after delaying M pulse time domain samples in coherent accumulation time after two pulse repetition time intervals1M multiplied by 1 dimensional radar echo signal matrix x received at Nth array element and L distance units after M pulse time domain samples in coherent accumulation time after two pulse repetition time intervals lag "N(ii) a And divide intoRespectively calculating M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval, and then receiving M multiplied by N by L dimensional radar echo signal matrixes X 'at N array elements and L range units, and M multiplied by N by L dimensional radar echo signal matrixes X' at N array elements and L range units after M pulse time domain samples in a coherent accumulation time after two pulse repetition time intervals, wherein the expressions are respectively as follows:
step 3, respectively calculating M pulse time domain samples in a coherent accumulation time, a P multiplied by L dimension radar echo signal power matrix Y after P point discrete Fourier transform, M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval, and M multiplied by L dimension radar echo signal matrixes X ' after P point discrete Fourier transform in N array elements and N array elements according to M multiplied by L dimension radar echo signal matrixes X ' after M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval and M multiplied by N dimension radar echo signal matrixes X ' received at N array elements and L distance units after M pulse time domain samples in a coherent accumulation time after two pulse repetition time intervals, and M pulse time domain samples in N array elements after P point discrete Fourier transform, A power matrix Y 'of the P multiplied by L dimensional radar echo signals received at the L distance units, and a power matrix Y' of the P multiplied by L dimensional radar echo signals received at the L distance units, N array elements after P point discrete Fourier transform and M pulse time domain samples in coherent accumulation time after delaying two pulse repetition time intervals; wherein, P represents the point number of discrete Fourier transform, and L represents the maximum unambiguous range unit number of the airborne radar.
The specific substeps of step 3 are:
3.1 respectively converting the M multiplied by N multiplied by L dimensional radar echo signal matrix X after the time domain sampling of M pulses in coherent accumulation time into the M multiplied by L dimensional radar echo signal matrix after the time domain sampling of M pulses in coherent accumulation timeConverting an M multiplied by N multiplied by L dimensional radar echo signal matrix X' received at N array elements and L range units after M pulse time domain samples within a coherent accumulation time after a pulse repetition time interval into an M multiplied by L dimensional radar echo signal matrix received at N array elements and L range units after M pulse time domain samples within a coherent accumulation time after a pulse repetition time intervalConverting an M multiplied by N multiplied by L dimensional radar echo signal matrix X' received at N array elements and L range units after M pulse time domain samples within a coherent accumulation time after two pulse repetition time intervals into an M multiplied by L dimensional radar echo signal matrix received at N array elements and L range units after M pulse time domain samples within a coherent accumulation time after two pulse repetition time intervalsThe expressions are respectively:
wherein, the first column of the M multiplied by L dimensional radar echo signal matrix X after the time domain sampling of M pulses in a coherent accumulation time isDimension M × 1, notedColumn I M x 1 dimensional radar echo signal vector
The mean value of the radar echo signals received at N array elements and the l-th distance unit after M pulse time domain samples in coherent accumulation time is shown,xn,lrepresenting radar echo signals received at an nth array element and an l-th distance unit after M pulse time domain samples in coherent accumulation time; m multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after M pulse time domain samples in coherent accumulation time after one pulse repetition time intervalColumn of (1) isDimension M × 1, notedColumn I M x 1 dimensional radar echo signal vector
The mean value of M multiplied by L dimensional radar echo signals received at N array elements and the first distance unit after M pulse time domain samples in coherent accumulation time lags behind one pulse repetition time interval is shown,x'n,lrepresenting M multiplied by L dimensional radar echo signals received at an nth array element and an L distance unit after M pulse time domain samples in coherent accumulation time after a pulse repetition time interval; m dimension radar echo signal matrix received at N array elements and L distance units after M pulse time domain samples in coherent accumulation time after two pulse repetition time intervals lagColumn of (1) isDimension M × 1, notedColumn I M x 1 dimensional radar echo signal vector
The mean value of M-dimensional radar echo signals of an M multiplied by L-dimensional radar echo signal matrix received at N array elements and the first distance unit after M pulse time domain samples in coherent accumulation time lagged by two pulse repetition time intervals is shown,x"n,land M dimension radar echo signals of an M multiplied by L dimension radar echo signal matrix received at the nth array element and the L distance unit after M pulse time domain samples in coherent accumulation time after two pulse repetition time intervals lag.
3.2 are respectively pairedColumn I M x 1 dimensional radar echo signal vectorPerforming P-point Discrete Fourier Transform (DFT) to obtainColumn I P x 1 dimensional radar echo signal vector
To pairColumn I M x 1 dimensional radar echo signal vectorPerforming P-point Discrete Fourier Transform (DFT) to obtainColumn I P x 1 dimensional radar echo signal vector
To pairColumn I M x 1 dimensional radar echo signal vectorPerforming P-point Discrete Fourier Transform (DFT) to obtainColumn I P x 1 dimensional radar echo signal vector
Sequentially taking 1 to L from L to obtain1 st column of P × 1 dimensional radar echo signal vectorToThe L column of the P x 1 dimensional radar echo signal vectorAnd1 st column of P × 1 dimensional radar echo signal vectorToThe L column of the P x 1 dimensional radar echo signal vectorAnd1 st column of P × 1 dimensional radar echo signal vectorToThe L column of the P x 1 dimensional radar echo signal vectorAnd then respectively obtaining a P multiplied by L dimensional radar echo signal matrix after sampling M pulse time domains in a coherent accumulation time of P point DFTP multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after M pulse time domain samples in coherent accumulation time after P point DFT lags one pulse repetition time intervalP multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after M pulse time domain samples in coherent accumulation time after two delayed pulse repetition time intervals of P point DFTThe expressions are respectively:
3.3 separately sampling the M pulse time domains in the coherent accumulation time of the P point DFT to obtain the P multiplied by L dimensional radar echo signal matrixAnd a P multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after M pulse time domain samples in coherent accumulation time after a pulse repetition time interval lagged by P point DFTAnd a P multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after M pulse time domain samples in coherent accumulation time after two delayed pulse repetition time intervals of P point DFTThe squares of absolute values of each element contained in the data are respectively obtained to obtain M pulse time domain samples in a coherent accumulation time, a P multiplied by L dimensional radar echo signal power matrix Y after P point discrete Fourier transform, M pulse time domain samples in a coherent accumulation time after delaying one pulse repetition time interval, a P multiplied by L dimensional radar echo signal power matrix Y' received at N array elements and L distance units after P point discrete Fourier transform, and P multiplied by L dimensional radar echo signal power received at N array elements and L distance units after M pulse time domain samples in a coherent accumulation time after delaying two pulse repetition time intervals, P point discrete Fourier transformMatrix Y ", whose expressions are:
wherein, the L column of a power matrix Y of the P multiplied by L dimensional radar echo signals after M pulse time domain samples and P point discrete Fourier transform in a coherent accumulation time is Y (L),
representing P multiplied by L dimensional radar echo signal matrix after M pulse time domain samples and P point discrete Fourier transform in one coherent accumulation time of P point DFTRow p, column l; the L column of a power matrix Y 'of the P multiplied by L dimensional radar echo signals received at N array elements and L distance units after M pulse time domain samples and P point discrete Fourier transform in coherent accumulation time lags one pulse repetition time interval is Y' (L),
representing a P multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after P point discrete Fourier transform and M pulse time domain samples in coherent accumulation time after P point DFT lags one pulse repetition time intervalRow p, column l; the L column of a power matrix Y 'of the P multiplied by L dimensional radar echo signals received at N array elements and L distance units after M pulse time domain samples and P point discrete Fourier transform in a coherent accumulation time lag two pulse repetition time intervals is Y' (L),
representing P multiplied by L dimensional radar echo signal matrix received at N array elements and L distance units after P point discrete Fourier transform and M pulse time domain samples in coherent accumulation time after two delayed pulse repetition time intervals of P point DFTRow p, column l; p is 1,2, …, P represents the number of discrete fourier transform points, L is 1,2, …, L represents the maximum number of unambiguous range units of the airborne radar.
Step 4, performing main clutter suppression processing on the M pulse time domain samples in the coherent accumulation time, the P multiplied by L dimensional radar echo signal power matrix Y after P point discrete Fourier transform, the M pulse time domain samples in the coherent accumulation time after lagging one pulse repetition time interval, the P multiplied by L dimensional radar echo signal power matrix Y 'received at the N array elements and the L distance units after P point discrete Fourier transform, and the M pulse time domain samples in the coherent accumulation time after lagging two pulse repetition time intervals, the P multiplied by L dimensional radar echo signal power matrix Y' received at the N array elements and the L distance units after P point discrete Fourier transform according to a three-pulse cancellation method to obtain M pulse time domain samples in the coherent accumulation time after main clutter suppression processing and a P multiplied by L dimensional radar echo signal matrix Z after P point discrete Fourier transform, and then calculating a PL multiplied by 1 dimensional radar echo signal matrix Z' after M pulse time domain samples and P point discrete Fourier transform in the sequenced coherent accumulation time.
Specifically, according to a three-pulse cancellation method, performing main clutter suppression on M pulse time domain samples in one coherent accumulation time, a P multiplied by L dimensional radar echo signal power matrix Y after P-point discrete Fourier transform, a P multiplied by L dimensional radar echo signal power matrix Y 'received at N array elements and L distance units after P-point discrete Fourier transform and a P multiplied by L dimensional radar echo signal power matrix Y' received at N array elements and L distance units after M pulse time domain samples in one coherent accumulation time after two pulse repetition time intervals and P-point discrete Fourier transform to obtain a P multiplied by L dimensional radar echo signal matrix Z after M pulse time domain samples in one coherent accumulation time and P-point discrete Fourier transform after main clutter suppression, for estimating a noise power level; the P multiplied by L dimensional radar echo signal matrix Z after M pulse time domain sampling and P point discrete Fourier transform in a coherent accumulation time after the main clutter processing is suppressed has the following expression:
the elements of the P row and the L column of a P multiplied by L dimensional radar echo signal matrix Z after inhibiting M pulse time domain samples and P point discrete Fourier transform in coherent accumulation time after main clutter processing are Zp,lThe calculation formula is:
wherein P is 1,2, …, P represents the point number of discrete fourier transform, and P also represents the total number of doppler channels; l is 1,2, …, L represents the maximum unambiguous range bin number of the airborne radar.
The P multiplied by L dimensional radar echo signal matrix Z subjected to M pulse time domain sampling and P point discrete Fourier transform in coherent accumulation time after the suppression of the main clutter comprises P multiplied by L range-Doppler channels, each range-Doppler channel corresponds to a range-Doppler value, so that the P multiplied by L dimensional radar echo signal matrix Z used for estimating the noise power level after the suppression of the main clutter comprises P multiplied by L range-Doppler values, the P multiplied by L range-Doppler values are sorted from small to large to obtain M pulse time domain sampling in the sorted coherent accumulation time and a PL multiplied by 1 dimensional radar echo signal matrix Z 'subjected to P point discrete Fourier transform, the M pulse time domain sampling in the sorted coherent accumulation time and the PL multiplied by 1 dimensional radar echo signal matrix Z' subjected to P point discrete Fourier transform comprise PL elements, are respectively recorded as z'1To z'PLAnd satisfy z'1≤z'2≤…≤z'f≤…≤z'PL，f∈{1,2,…,PL}，z'fAnd f, representing the f element in a PL multiplied by 1 dimensional radar echo signal matrix Z' after M pulse time domain samples and P point discrete Fourier transform in the sequenced coherent accumulation time.
And 5, calculating to obtain a fitting curve of elements in the PL x 1 dimensional radar echo signal matrix Z' after the P-point discrete Fourier transform and the M pulse time domain samples in the coherent accumulation time based on least square, wherein the element is under a two-dimensional real number coordinate.
Specifically, a PL x 1 dimensional radar echo signal matrix Z' obtained by time domain sampling of M pulses and discrete Fourier transform of P points in a sequenced coherent accumulation time is placed in a two-dimensional real number coordinate system to obtain PL points in the two-dimensional real number coordinate system, wherein the f < th > pointThe abscissa of the point in the two-dimensional real number coordinate system is f, and the ordinate of the f-th point in the two-dimensional real number coordinate system is z'f，f＝1,2,…,PL。
Setting PL points in the two-dimensional real number coordinate system to be on a curve satisfying a polynomial relationship, namely, for an element Z 'at an arbitrary position k in a matrix Z'kK is 1,2, …, PL, element z'kThe following relationship is satisfied on the curve:
F(z'k)＝θ0+θ1(k)2+…+θw(k)w-1…+θW(k)W-1
wherein, F (z'k) Represents an element z'kCorresponding polynomial to be solved, theta0,θ1,…θWRespectively element z'kThe coefficient of each term in the corresponding polynomial to be solved; thetawRepresents z'kThe coefficient of a term of order w in the corresponding polynomial to be solved, w representing z'kThe order of each term in the corresponding polynomial to be solved, W ═ 0,1, …, W-1, W denotes z'kThe corresponding polynomial to be solved contains an order, and W generally takes a value of 5-9; z'kAnd (3) representing the element at the position k in the PL multiplied by 1 dimensional radar echo signal matrix Z' after M pulse time domain samples and P point discrete Fourier transform in the sequenced coherent accumulation time.
K is respectively taken as 1 to PL to obtain element z'1Corresponding polynomial F (z'1) To element z'PLCorresponding polynomial F (z'PL) And recording the polynomial as PL polynomials to be solved, and respectively calculating to obtain a P multiplied by L dimensional order matrix K and a W multiplied by 1 dimensional coefficient matrix theta of the PL polynomials to be solved, wherein the expressions are respectively:
the expanded expression of Z ═ K θ is:
in fact, for PL × 1-dimensional radar echo signal matrix Z' after M pulse time domain sampling and P-point discrete fourier transform in a coherent accumulation time after sorting, it is difficult to calculate an analytic solution of the W × 1-dimensional coefficient matrix θ of PL polynomials to be solved, so that here, linear least squares are used to calculate an estimated value of the W × 1-dimensional coefficient matrix θ of PL polynomials to be solvedThe expression is as follows:
further, the estimated values of the W multiplied by 1 dimensional coefficient matrix theta of PL polynomial to be solved are obtained respectivelyEstimated value of medium W coefficientsAnd calculating to obtain a fitting curve f (F) (k) of elements in a PL multiplied by 1 dimensional radar echo signal matrix Z' under a two-dimensional real number coordinate after sequencing M pulse time domain samples and P point discrete Fourier transform based on least square in a coherent accumulation time,the value range of k is more than or equal to 1 and less than or equal to PL.
And 6, solving the slope of a fitting curve of elements in a PL x 1 dimensional radar echo signal matrix Z' under a two-dimensional real number coordinate after the sorting of M pulse time domain samples and P point discrete Fourier transform based on least square, finding a slope minimum value point, and taking a power value corresponding to the slope minimum value point as airborne radar noise power under a clutter background based on polynomial fitting.
Specifically, the fitted curve is determined as Estimated values of W x 1 dimensional coefficient matrix theta for PL polynomials to be solvedThe value range of k is more than or equal to 1 and less than or equal to PL, and the slope of the fitting curve F (k) is solvedAnd taking the minimum value of the slopeThen will beCorresponding position k when taking the minimum value0Substituting the power value corresponding to the minimum slope value into the fitting curve to obtain a power value corresponding to the minimum slope value, and taking the power value corresponding to the minimum slope value as the airborne radar noise power F (k) under the clutter background based on polynomial fitting0)。
Wherein, denotes the corresponding value when taking the minimum value,representing a partial derivation operation.
The effect of the present invention can be further illustrated by the following simulation experiments:
simulation conditions:
1) the number of array elements of an antenna array surface of the airborne radar is 20, an even linear array structure is adopted, the array elements are evenly arranged on the antenna array surface of the airborne radar, the distance between the array elements is d lambda/2, lambda is the carrier wave wavelength of the airborne radar, the number of pulses of the airborne radar in a coherent accumulation period in a simulation experiment is 64, and the number of maximum unambiguous distance units of the airborne radar is 1000.
2) Echo data of a simulation experiment are generated according to simulation of a clutter model proposed by a Lincoln laboratory J.Ward, Gaussian white noise is added, in order to simulate an environment with strong clutter and low repetition frequency and difficulty in estimating noise power, the pulse repetition frequency is set to be 2000Hz, the clutter noise power ratio is 50dB, and detailed simulation parameters are shown in the following table 1:
TABLE 1
2. Simulation content and result analysis
In order to verify the effectiveness of the method, the simulation experiment selects radar echo data received under the conditions of low repetition frequency and strong clutter power of an airborne radar, and performs pulse-Doppler processing and pulse cancellation processing on the radar echo data, and on the basis, the noise power level is estimated according to the method, and the result is shown in fig. 2a and 2b, wherein fig. 2a is a distribution diagram of power obtained after the radar echo data is subjected to pulse-Doppler processing along the direction of a range gate and the direction of a Doppler channel respectively, wherein the abscissa is a Doppler channel number, the ordinate is a range gate number, and each point represents the power of the position; fig. 2b is a power distribution diagram obtained after the radar echo data is sequentially subjected to pulse-doppler processing and pulse cancellation processing, wherein the abscissa is a doppler channel number, the ordinate is a range gate number, and each point represents the power of the point.
Then, the power curves of the power distribution in fig. 2a and the power distribution in fig. 2b, which are averaged in the distance direction, and the noise power curve estimated by using the method of the present invention and the actual noise power curve are obtained as graphs of the noise power levels obtained by using different processing methods, which are averaged in the distance direction, respectively, and the noise power curve estimated by using the method of the present invention and the actual noise power curve, respectively, as shown in fig. 3, and fig. 3 is a graph of the noise power levels obtained by using different processing methods, which are averaged in the distance direction, respectively, of the power distribution in fig. 2a and the power distribution in fig. 2b, which are averaged in the distance direction, respectively, and the noise power curve estimated by using the method of the present invention and the actual noise.
As can be seen from fig. 2a, under the conditions that the clutter environment is severe (the clutter power is strong) and the clutter fills the doppler space (the radar pulse repetition frequency is low), the main lobe and the side lobe of the clutter occupy most of the range-doppler diagram, it is difficult to find an intuitive area where only noise exists to estimate the noise power, and the noise estimation robustness is difficult to ensure due to the diffusion of the clutter power in the doppler direction caused by the pulse-doppler processing.
As can be seen from fig. 2b, after the method of the present invention uses the triple-pulse cancellation method to suppress the main clutter, the noise power level is not changed like the space-time adaptive processing, and the clutter is suppressed to a certain extent, so that the subsequent noise power estimation can be more accurate.
As can be seen from fig. 3, under the set simulation condition, it is difficult to obtain a curve obtained by directly averaging the distance according to the data processed by the pulse-doppler processing, and the difference between the lowest point of the curve and the actual noise power is about 10dB, which indicates that the noise power cannot be simply estimated under the condition; the difference between the noise power level estimated by using the method of the invention and the actual noise power is only about 2dB, which shows that the method of the invention can still accurately estimate the noise power even under the conditions that the clutter is stronger, the pulse repetition frequency is lower and the noise area is difficult to find from the pulse-Doppler diagram, thereby bringing better target detection performance after space-time adaptive processing.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention; thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (4)
1. A method for estimating radar noise power under clutter background based on polynomial fitting is characterized by comprising the following steps:
step 1, determining an airborne radar, wherein the airborne radar transmits a pulse signal, the pulse repetition time interval of the pulse signal transmitted by the airborne radar is PRI, and the pulse width of the pulse signal transmitted by the airborne radar is TpThe pulse repetition frequency of the airborne radar transmitting pulse signal is PRF; the number of array elements of an antenna array surface of the airborne radar is N, the number of pulses of the airborne radar in a coherent accumulation period is M, and the airborne radar isThe maximum number of unambiguous range cells is L,calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X after the time domain sampling of M pulses in coherent accumulation time;
step 2, respectively calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X 'received at N array elements and L distance units after M pulse time domain samples within a coherent accumulation time after a pulse repetition time interval and an M multiplied by N multiplied by L dimensional radar echo signal matrix X' received at N array elements and L distance units after M pulse time domain samples within a coherent accumulation time after two pulse repetition time intervals;
step 3, respectively calculating M pulse time domain samples in a coherent accumulation time, a P multiplied by L dimension radar echo signal power matrix Y after P point discrete Fourier transform, M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval, and M multiplied by L dimension radar echo signal matrixes X ' after P point discrete Fourier transform in N array elements and N array elements according to M multiplied by L dimension radar echo signal matrixes X ' after M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval, and M multiplied by N by L dimension radar echo signal matrixes X ' received at N array elements and L distance units after M pulse time domain samples in a coherent accumulation time after two pulse repetition time intervals, The method comprises the following steps that a power matrix Y ' of a P multiplied by L dimensional radar echo signal received by L range units and a power matrix Y ' of the P multiplied by L dimensional radar echo signal received by L range units are obtained, wherein the power matrix Y ' of the P multiplied by L dimensional radar echo signal is obtained after P point discrete Fourier transform and M pulse time domain samples in coherent accumulation time lag two pulse repetition time intervals; wherein P represents the point number of discrete Fourier transform, and L represents the maximum unambiguous range unit number of the airborne radar;
step 4, carrying out main clutter suppression processing on M pulse time domain samples in the coherent accumulation time, a P multiplied by L dimensional radar echo signal power matrix Y after P point discrete Fourier transform, a P multiplied by L dimensional radar echo signal power matrix Y 'received at N array elements and L distance units after P point discrete Fourier transform and M pulse time domain samples in a coherent accumulation time after lagging a pulse repetition time interval, and a P multiplied by L dimensional radar echo signal power matrix Y' received at N array elements and L distance units after P point discrete Fourier transform and M pulse time domain samples in a coherent accumulation time after lagging two pulse repetition time intervals to obtain M pulse time domain samples in a coherent accumulation time after main clutter suppression processing and a P multiplied by L dimensional radar echo signal matrix Z after P point discrete Fourier transform, further calculating a PL multiplied by 1 dimensional radar echo signal matrix Z' after M pulse time domain samples and P point discrete Fourier transform in the sequenced coherent accumulation time;
step 5, calculating to obtain a fitted curve of elements in a PL x 1 dimensional radar echo signal matrix Z' subjected to the M pulse time domain samples and the P point discrete Fourier transform in the coherent accumulation time based on least square in a two-dimensional real number coordinate;
the process of step 5 is:
placing a PL x 1 dimensional radar echo signal matrix Z 'subjected to M pulse time domain sampling and P point discrete Fourier transform in the sequenced coherent accumulation time into a two-dimensional real number coordinate system to obtain PL points in the two-dimensional real number coordinate system, wherein the abscissa of the f-th point in the two-dimensional real number coordinate system is f, and the ordinate of the f-th point in the two-dimensional real number coordinate system is Z'f，f＝1，2，…，PL；
Setting PL points in the two-dimensional real number coordinate system to be on a curve satisfying a polynomial relationship, namely, for an element Z 'at an arbitrary position k in a matrix Z'kK is 1,2, …, PL, element z'kThe following relationship is satisfied on the curve:
F(zk)＝θ0+θ1(k)2+···+θw(k)w-1···+θW(k)W-1
wherein, F (z)k) Represents an element z'kCorresponding polynomial to be solved, theta0，θ1，…θWRespectively represent the element z'kThe coefficient of each term in the corresponding polynomial to be solved; thetawRepresents z'kThe coefficient of a term of order w in the corresponding polynomial to be solved, w representing z'kThe order of each term in the corresponding polynomial to be solved, W ═ 0,1, …, W-1, W denotes z'kThe order contained by the corresponding polynomial to be solved; z'kRepresenting the elements at the position k in a PL multiplied by 1 dimensional radar echo signal matrix Z' after M pulse time domain samples and P point discrete Fourier transform in the sequenced coherent accumulation time;
k is respectively taken as 1 to PL to obtain element z'1Corresponding polynomial F (z'1) To element z'PLCorresponding polynomial F (z'PL) And recording the polynomial as PL polynomials to be solved, and respectively calculating to obtain a P multiplied by L dimensional order matrix K and a W multiplied by 1 dimensional coefficient matrix theta of the PL polynomials to be solved, wherein the expressions are respectively:
the expanded expression of Z ═ K θ is:
then, the estimated value of the W x 1 dimensional coefficient matrix theta of PL polynomials to be solved is calculated by using linear least squaresThe expression is as follows:
to obtain W x 1 dimensional coefficient matrix theta of PL polynomial to be solvedEstimated valueEstimated value of medium W coefficientsAnd calculating to obtain a fitting curve f (F) (k) of elements in a PL multiplied by 1 dimensional radar echo signal matrix Z' under a two-dimensional real number coordinate after sequencing M pulse time domain samples and P point discrete Fourier transform based on least square in a coherent accumulation time,the value range of k is more than or equal to 1 and less than or equal to PL;
and 6, solving the slope of a fitting curve of elements in a PL x 1 dimensional radar echo signal matrix Z' under a two-dimensional real number coordinate after the sorting of M pulse time domain samples and P point discrete Fourier transform based on least square, finding a slope minimum value point, and taking a power value corresponding to the slope minimum value point as airborne radar noise power under a clutter background based on polynomial fitting.
2. The method of claim 1, wherein in step 1, the maximum number of unambiguous range units of the airborne radar is L, b represents the receiving bandwidth of the airborne radar;
the M multiplied by N multiplied by L dimensional radar echo signal matrix X after the time domain sampling of M pulses in the coherent accumulation time has the expression:
n is 1,2, …, N, L is 1,2, …, L, N represents the number of array elements included in the antenna array of the airborne radar, and M represents the number of pulses of the airborne radar in a coherent accumulation period; recording radar echo signals received at the nth array element and the l-th distance unit after the mth pulse time domain sampling in coherent accumulation time as xm，n，lAnd enabling M to respectively take 1 to M, and further calculating to obtain an M multiplied by 1 dimensional radar echo signal matrix x received at an nth array element and a l distance unit after M pulse time domain samples in coherent accumulation timen，lThe expression is as follows:
which represents the normalized doppler frequency of the doppler signal,v denotes the speed of the airborne radar and λ denotes the wavelength of the electromagnetic wave signal emitted by the airborne radar.
3. The method for estimating the power of the radar noise in the clutter background based on the polynomial fitting according to claim 2, wherein the process of the step 2 is as follows:
respectively delaying time domain sampling points by a pulse repetition time interval and two pulse repetition time intervals, then sampling M pulse time domains in coherent accumulation time, and receiving an Mx1 dimensional radar echo signal matrix x at an nth array element and an l distance unitn，lRespectively carrying out time domain sampling to respectively obtain M multiplied by 1 dimensional radar echo signal matrixes x 'received at the nth array element and the l distance unit after M pulse time domain samples in coherent accumulation time lagging one pulse repetition time interval'n，lAnd M multiplied by 1 dimensional radar echo signal matrix x' received at the nth array element and the l distance unit after delaying M pulse time domain samples in coherent accumulation time after two pulse repetition time intervalsn，lThe expressions are respectively:
when n is 1, respectively taking 1 to L for L, and further respectively obtaining M multiplied by 1 dimensional radar echo signal matrixes x 'received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after one pulse repetition time interval'1And M multiplied by 1 dimensional radar echo signal matrix x' received at the 1 st array element and L distance units after delaying M pulse time domain samples in a coherent accumulation time after two pulse repetition time intervals1(ii) a The M x 1-dimensional radar echo signal matrix x 'received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after lagging one pulse repetition time interval'1Is an M x 1 dimensional radar echo signal matrix x 'received at the 1 st array element and the 1 st range unit after M pulse time domain samples in a coherent accumulation time after a pulse repetition time interval'1，1M x 1-dimensional radar echo signal matrix x 'received at 1 st array element and L distance unit after M pulse time domain samples in coherent accumulation time after lagging one pulse repetition time interval'1，L(ii) a M multiplied by 1 dimensional radar echo signal matrix x' received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after delaying two pulse repetition time intervals1The method is characterized in that an M x 1 dimensional radar echo signal matrix x' received at the 1 st array element and the 1 st distance unit after M pulse time domain samples in coherent accumulation time after delaying two pulse repetition time intervals1，1M x 1 dimensional radar echo signal matrix x' received at the 1 st array element and the L-th distance unit after M pulse time domain samples in coherent accumulation time after lagging two pulse repetition time intervals1，L；
Then N is respectively taken from 2 to N, and M multiplied by 1 dimensional radar echo signal matrixes x 'received at the 1 st array element and L distance units after M pulse time domain samples in coherent accumulation time after a pulse repetition time interval are obtained respectively'1M x 1-dimensional radar echo signal matrix x 'received at Nth array element and L distance units after M pulse time domain samples in coherent accumulation time after lagging one pulse repetition time interval'NAnd M multiplied by 1 dimensional radar echo signal matrix x' received at the 1 st array element and L distance units after delaying M pulse time domain samples in coherent accumulation time after two pulse repetition time intervals1M multiplied by 1 dimensional radar echo signal matrix x' received at Nth array element and L distance units after M pulse time domain samples in coherent accumulation time after lagging two pulse repetition time intervalsN(ii) a Respectively calculating to obtain an M multiplied by N multiplied by L dimensional radar echo signal matrix X 'received at N array elements and L distance units after M pulse time domain samples within a coherent accumulation time after a pulse repetition time interval and an M multiplied by N multiplied by L dimensional radar echo signal matrix X' received at N array elements and L distance units after M pulse time domain samples within a coherent accumulation time after two pulse repetition time intervals, wherein the expressions are respectively as follows:
4. the method of claim 1, wherein the method of estimating the power of the radar noise in the clutter background based on the polynomial fitting,in step 6, the airborne radar noise power in the clutter background based on the polynomial fitting is F (k)0)， Denotes the corresponding value when taking the minimum value,representing a partial derivation operation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610964932.7A CN106546966B (en) | 2016-10-31 | 2016-10-31 | Radar noise power estimation method under clutter background based on fitting of a polynomial |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610964932.7A CN106546966B (en) | 2016-10-31 | 2016-10-31 | Radar noise power estimation method under clutter background based on fitting of a polynomial |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106546966A CN106546966A (en) | 2017-03-29 |
| CN106546966B true CN106546966B (en) | 2019-03-29 |
Family
ID=58395305
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610964932.7A Active CN106546966B (en) | 2016-10-31 | 2016-10-31 | Radar noise power estimation method under clutter background based on fitting of a polynomial |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106546966B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109164427B (en) * | 2018-09-07 | 2023-03-24 | 西安电子科技大学 | Method for detecting noise power of radar receiver |
| CN109375197B (en) * | 2018-10-23 | 2023-02-10 | 哈尔滨工程大学 | Small-size vector array low-frequency scattering correction method |
| CN112684418B (en) * | 2020-12-22 | 2024-04-16 | 苏州度风科技有限公司 | Weak signal extraction method of pulse Doppler radar echo |
| CN114966568B (en) * | 2022-05-25 | 2024-06-25 | 西安电子科技大学 | Space-time adaptive processing method for weight vector time-varying even acceleration flying radar |
| CN116106852B (en) * | 2023-04-12 | 2023-07-14 | 中国人民解放军63921部队 | Method and device for determining airborne main clutter channel and electronic equipment |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8912951B2 (en) * | 2012-10-09 | 2014-12-16 | Raytheon Company | Moving target detection using a two-dimensional folding approach |
| CN104459657B (en) * | 2014-06-19 | 2017-01-25 | 西安电子科技大学 | Extension factorization space-time two-dimensional self-adaptive processing method based on data fitting |
| CN104237883B (en) * | 2014-09-15 | 2017-02-01 | 西安电子科技大学 | Airborne radar space time self-adaptation processing method with sparse representation |
| US10061016B2 (en) * | 2014-12-29 | 2018-08-28 | Texas Instruments Incorporated | Phase noise measurement in a cascaded radar system |
| CN105510887B (en) * | 2015-12-22 | 2018-02-02 | 西安电子科技大学 | To the active suppressing formula disturbance restraining method of airborne radar under a kind of clutter background |
-
2016
- 2016-10-31 CN CN201610964932.7A patent/CN106546966B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN106546966A (en) | 2017-03-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106546966B (en) | Radar noise power estimation method under clutter background based on fitting of a polynomial | |
| CN106546965B (en) | Space-time adaptive processing method based on radar amplitude and Doppler-frequency estimation | |
| CN107976660B (en) | Missile-borne multi-channel radar ultra-low-altitude target analysis and multi-path echo modeling method | |
| CN104360325B (en) | Space-time adaptive processing method for airborne forward-looking array radar | |
| CN105445701B (en) | The pulse angle estimating method of DDMA MIMO radar targets | |
| CN103364772B (en) | Target low elevation estimation method based on real number field generalized multiple-signal sorting algorithm | |
| CN106772253B (en) | Radar clutter suppression method under non-uniform clutter environment | |
| CN102955150B (en) | SAR (synthetic aperture radar) direction ambiguity suppression method based on antenna main lobe dominance intensity constraint | |
| CN109613532B (en) | Airborne radar real-time Doppler beam sharpening super-resolution imaging method | |
| CN103018727A (en) | Sample-training-based non-stationary clutter suppression method of vehicle-mounted radar | |
| CN103913725B (en) | Airborne radar Ground moving targets detection method under intensive repeating jamming environment | |
| CN108037494B (en) | Radar target parameter estimation method under impulse noise environment | |
| CN104166136A (en) | Interference subspace tracking-based high-efficiency self-adaptive monopulse angle measurement method | |
| CN103197294B (en) | Elevation angle estimating method of multi-frequency fusion maximum likelihood low-altitude target | |
| CN108387884B (en) | Airborne radar clutter suppression method based on knowledge-assisted sparse progressive minimum variance | |
| CN103954941B (en) | The multipulse cognitive clutter suppression method of a kind of airborne phased array radar two dimension | |
| CN103760529A (en) | Efficient cascading space-time adaptive processing method based on passive detection | |
| CN112612006B (en) | Deep learning-based non-uniform clutter suppression method for airborne radar | |
| CN108020817A (en) | Air-borne Forward-looking battle array radar clutter suppression method based on registration | |
| Rabideau | Clutter and jammer multipath cancellation in airborne adaptive radar | |
| CN113093120A (en) | Method for estimating PRI agile radar target parameters based on capon algorithm | |
| CN111239677A (en) | Multi-beam passive monopulse angle measurement method based on digital array | |
| Chen et al. | Suppression method for main-lobe interrupted sampling repeater jamming in distributed radar | |
| Xue et al. | Knowledge-based target detection in compound Gaussian clutter with inverse Gaussian texture | |
| CN103760540B (en) | Based on moving target detect and the method for parameter estimation of reconstruction signal and 1-norm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |